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Hybrid remote, metro-based senior Snowflake data engineer role with popular data-engineer title increases competition.
Snowflake and cloud-specific skills are transferable but platform specialization raises sensitivity.
Multiple mandatory technical skills, certifications, and 7+ years experience indicate strict shortlisting.
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Design, develop, and maintain scalable data pipelines and ELT/ETL workflows using Snowflake, SQL, Python, Snowpark, and dbt.
Optimize Snowflake performance and costs via query tuning, warehouse sizing, clustering, workload management, and automation of suspend/resume.
Implement orchestration, dependency management, monitoring, error handling, and enhance data quality, lineage, and documentation in production-grade environments.
7+ years of experience in Data Engineering with significant hands-on Snowflake expertise.
Advanced SQL skills including complex transformations and stored procedures; strong Python development experience.
Hands-on experience with Snowpark, Dynamic Tables, Streams, Tasks, and building production ELT/ETL pipelines.
Experience with at least one major cloud platform (AWS, Azure, or GCP); familiarity with Git, CI/CD, and automated testing.
Senior-level data engineer with deep Snowflake and cloud-based enterprise environment experience.
Experience modernizing data workloads using reusable engineering patterns and advanced Snowflake features.
Comfortable collaborating in Agile settings with architects, DevOps, analysts, and stakeholders to deliver production-ready scalable solutions.